Several methanogenic
pathways in oxic surface waters were recently discovered, but their relevance
in the natural environment is still unknown. Our study examines distinct
methane (CH4) enrichments that repeatedly occur below the thermocline during the
summer months in the central Baltic Sea. In agreement with previous studies
in this region, we discovered differences in the methane distributions
between the western and eastern Gotland Basin, pointing to in situ methane
production below the thermocline in the latter (concentration of CH4 14.1±6.1 nM, δ13CCH4−62.9 ‰). Through
the use of a high-resolution hydrographic model of the Baltic Sea, we showed
that methane below the thermocline can be transported by upwelling events
towards the sea surface, thus contributing to the methane flux at the
sea–air interface. To quantify zooplankton-associated methane production
rates, we developed a sea-going methane stripping-oxidation line to determine
methane release rates from copepods grazing on 14C-labelled
phytoplankton. We found that (1) methane production increased with the number
of copepods, (2) higher methane production rates were measured in incubations
with Temora longicornis (125±49 fmol methane copepod−1 d−1) than in incubations with
Acartia spp. (84±19 fmol CH4 copepod−1 d−1) dominated zooplankton
communities, and (3) methane was only produced on a Rhodomonas sp.
diet, and not on a cyanobacteria diet. Furthermore, copepod-specific methane
production rates increased with incubation time. The latter finding suggests
that methanogenic substrates for water-dwelling microbes are released by cell
disruption during feeding, defecation, or diffusion from fecal pellets. In
the field, particularly high methane concentrations coincided with stations
showing a high abundance of DMSP/DMSO-rich Dinophyceae. Lipid biomarkers extracted
from phytoplankton- and copepod-rich samples revealed that Dinophyceae are a
major food source of the T. longicornis dominated zooplankton
community, supporting the proposed link between copepod grazing, DMSP/DMSO
release, and the build-up of subthermocline methane enrichments in the
central Baltic Sea.

Climate change, caused by increased greenhouse gas concentrations in the
atmosphere, has an indisputable influence on societal and economical
evolution on local, regional and global scales. In order to better predict
future climate development, a more precise quantitative and mechanistic
understanding of individual sources and sinks of relevant greenhouse gases,
such as methane, is crucial. Methane as an atmospheric component has a
relevant impact on the earth's climate (Etminan et al., 2016; IPCC, 2013). In
general, biogenic sources of methane are associated with microorganisms
(Archaea) in anoxic habitats, for example, in the ocean and lake sediments,
wetlands, landfills, rice fields or the gastrointestinal tracts of termites
and ruminants (IPCC, 2013). However, recent studies demonstrated that
methanogenesis also occurs in oxic environments. These unconventional
methanogenic pathways are mediated by aerobic prokaryotes (Yao et al., 2016)
as well as eukaryotes, including plants (Keppler et al., 2006; Lenhart et
al., 2016), animals (Tuboly et al., 2013), lichens (Lenhart et al., 2015),
and fungi (Lenhart et al., 2012).

Methane concentrations in the oxygenated surface ocean and lake waters show
strong regional and seasonal fluctuations (e.g. Jakobs et al., 2014; Donis et
al., 2017). Large areas are supersaturated with methane and act as a net
source to the atmosphere (e.g. Bange et al., 1994; Lamontagne et al., 1973;
Tang et al., 2014). It is assumed that climate-driven modifications in
aquatic systems such as increasing water temperatures, enhanced
stratification, and nutrient limitation could further reinforce aquatic
methane production (Karl et al., 2008). Such modifications are particularly
important for shallow oxic methane production that largely bypasses microbial
methane consumption as it places the methane source close to the water
surface, intensifying fluxes to the atmosphere. However, the origin of
methane in the oxic upper water column is still unclear and hence also
referred to as the “methane paradox” (Scranton and Brewer, 1977).

The Baltic Sea is characterized by pronounced lateral gradients including
e.g. temperature, salinity, oxygen and methane concentrations, which
altogether strongly influence the biology of the ecosystem (Feistel et al.,
2008, and references therein). It consists of several sub-basins, of which
the eastern Gotland Basin is the largest. The eastern Gotland Basin has a
maximum depth of 248 m and establishes a seasonal thermocline at 10–30 m
water depth in the summer months, and a permanent halocline at 70–90 m
(Omstedt et al., 2004). In general, bottom waters in this basin are anoxic,
unless episodic inflow events of more saline and oxygen-rich North Sea water
into the deep basins lead to temporary oxic conditions (Franck et al., 1987;
Mohrholz et al., 2015).

Methane concentrations in the Baltic Sea tend to increase with depth due to
its release from the anoxic sediments (Schmale et al., 2010). However, recent
studies revealed a recurring methane accumulation in oxic waters right below
the thermocline during the summer months (Jakobs et al., 2014; Schmale et
al., 2018). Stable carbon isotopes indicated an in situ biogenic methane
origin, whereas clonal sequences pointed towards methanogenic Archaea as
potential producers (Schmale et al., 2018). It was further shown that
zooplankton-associated methane production contributed to the subthermocline
methane enrichment (Schmale et al., 2018). The authors found that methane
increased with increasing amounts of zooplankton and they suggested that
changes in the copepod community and food web structure may influence the
spatial heterogeneity of methane accumulation in the upper part of the water
column. However, zooplankton-associated methane production rates alone were
not sufficient to fully explain the observed methane enrichment. They
concluded that this was most likely a consequence of using incubations with
very dense and probably food-limited zooplankton communities (1000 times the
natural density), leading to results that are difficult to transfer into the
natural environment (Schmale et al., 2018). To overcome these experimental
deficits, we developed a methane stripping-oxidation line to study
zooplankton-associated methane production rates in the field. Our ship-based
incubation experiments were performed with different zooplankton communities
obtained from either the surface or from below the thermocline. We used
almost natural copepod densities (1.5–8.5 times the natural density), and
different diets of 14C-labelled phytoplankton. In conjunction with
field investigations of methane concentrations and plankton distributions,
the present study gives important insights into the controls of
zooplankton-associated methane production in the central Baltic Sea.

2.1 Hydrographical and chemical characteristics of the water column

During cruise AL483 on R/V Alkor in August 2016 in the central
Baltic Sea, seven stations in the western (TF0283, TF0284) and eastern (from
south to north: TF0250, TF0260, TF0271, TF0286, TF0285) Gotland Basin
(Fig. 1) were investigated. At each station, the hydrographical variables,
including temperature, salinity and oxygen concentrations, of the water
column were examined along vertical profiles using a SBE 911 plus CTD system
(Seabird Electronics, USA; see Sect. S1 in the
Supplement). In addition, the vertical methane distribution pattern and the
stable carbon isotope ratio of methane (δ13CCH4)
were measured to differentiate between regions affected and regions
unaffected by subthermocline methane production. For these studies,
subsamples were taken from the rosette water sampler and analysed in the home
laboratory using a purge and trap system for methane concentration
measurements and a continuous-flow isotope ratio mass spectrometer (IRMS) for
stable carbon isotope analyses (see Sect. S1). In
order to investigate whether station TF0284 was affected by coastal upwelling
during the time of sampling, we analysed the output of a numerical ocean
model, covering the North Sea/Baltic Sea. This hydrodynamical model computed
a reconstruction of the state of the Baltic Sea with a spatial resolution of
1 nautical mile and 50 vertical levels. Further details of the model are
given in Gräwe et al. (2015).

Figure 1Map of sampling stations in the western Gotland Basin (WGB) and the
eastern Gotland Basin (EGB). Symbols describe the sampling gear. Stations
with a distinct subthermocline methane enrichment are marked in red.

Surface water methane saturation is calculated following Eq. (1), where SV
is the saturation value, Cw the measured concentration of methane in
seawater and Cequi the concentration in equilibrium with the
atmosphere using the solubility coefficient given by Wiesenburg et
al. (1979).

(1)SV%=CwCequi⋅100

2.2 Plankton community and lipid biomarker analyses

Phytoplankton samples for water column community analysis were taken from the
10 L free-flow bottles at stations TF0271, TF0284 and TF0286 (Fig. 1). Equal
amounts of water from the mixed layer (depths: 0–1, 2.5, 5, 7.5 and 10 m)
were pooled in accordance with the guidelines of the Helsinki Commission
(HELCOM, 2017). At stations characterized by a distinct subthermocline
methane enrichment (TF0271, TF0260, TF0285 and TF0286), additional samples
were taken from the subthermocline chlorophyll a maximum at about 20 m
water depth. At station TF0271, three samples were taken on 12 and 18 August
to investigate the temporal variability in the community composition at this
location. All phytoplankton samples were transferred into 250 mL brown glass
bottles and preserved with 1 mL of acetic Lugol solution (2 % final
concentration). For later community analyses, 25 mL sub-samples were
concentrated in settling chambers (Utermöhl, 1958). They were counted
using an inverted microscope and the counts were converted into carbon
biomass using the cell volumes (Olenina et al., 2006; HELCOM, 2017).

Zooplankton samples for water column community analyses were collected with a
WP2 net (towed at 0.5 m s−1, mouth opening, 25 m2, mesh size
100 µm, according to HELCOM, 2017)
independent of daytime. Vertically integrated hauls from two depth intervals
were taken to obtain zooplankton samples: (i) thermocline to surface (e.g.
20–0 m, depending on the physical structure of the water column), and
(ii) halocline to thermocline (e.g. 60–20 m). The concentrated samples
(500 mL) were preserved in borax-buffered formalin (4 % final
concentration). For later copepod-specific community analyses, sub-samples
were counted using a compound microscope until at least 500 individual
copepods were taxonomically classified. Nauplii were pooled together for all
copepod species, while C1–C5 copepodite stages and adults were pooled for individual species. Finally, to
exclude potential daytime effects through vertical migration of the
zooplankton communities above the halocline, counts from both integrated
hauls were averaged according to the filtered volume. Similar to the
phytoplankton sampling strategy, three samples at TF0271 were taken in a
period of 10 days to investigate the temporal variability in the community
composition at this station.

Lipid biomarkers were analysed to obtain information on the trophic
relationships of copepods in the field at station TF0271 that showed a
distinct methane enrichment below the thermocline. For this purpose, their
putative food source, phytoplankton in the mixed layer, was sampled with an
Apstein net. The phytoplankton were separated from co-sampled zooplankton
using a simple self-built trap consisting of a 1.5 L transparent plastic
bottle with a closable outlet at the bottom. The zooplankton were attracted
towards the trap using a light source attached close to the outlet, and
drained off. Then the phytoplankton, which remained in the bottle, were
sampled. The target copepod T. longicornis has been known to migrate
diurnally from the light-penetrated surface layer towards greater depths to
escape predation (Hansen et al., 2006; Schmale et al., 2018). For lipid
biomarker studies, a concentrated sample of zooplankton rich in T. longicornis was retrieved, avoiding major co-sampling of phytoplankton. This
sampling was performed at station TF0271 by hauling a WP-2 net (see above) in
the subthermocline layer (25–60 m) during the daytime. For comparison, a
zooplankton sample was taken at station TF0250 without a distinct methane
enrichment below the thermocline. Here, the community composition was low in
T. longicornis and instead was dominated by Acartia spp.
and Pseudocalanus spp. All samples were concentrated by sieving
(20 µm) and kept frozen until further workup in the home
laboratory. The samples were lyophilized and extracted
(3×, ultrasound, 15 min, 20 ∘C) with dichloromethane
(DCM) ∕ methanol (MeOH) (2:1, v:v), DCM ∕ MeOH (3:1, v:v) and
DCM ∕n-hexane (2:1, v:v). From the resulting total organic
extract, neutral lipids (NL, largely containing storage lipids such as
triglycerides, wax esters, and sterols) were separated using silica gel
column chromatography by elution with DCM ∕ acetone (9:1, v:v). After
drying, fatty acids (FA) in the NL fraction were transesterified by reaction
with trimethylchlorosilane (TMCS) ∕ MeOH (1:9, v:v; 90 min,
80 ∘C). After partitioning into n-hexane (3×, 1 mL) and
drying, alcohols contained in the NL were converted to their trimethylsilyl
(TMS-) derivatives by reacting with 200 µl of a
n-hexane/BSTFA/pyridine mixture (5:3:2, v:v:v; 40 ∘C,
60 min). The derivatized NL fractions were analysed by coupled gas
chromatography–mass spectrometry (GC–MS), as described elsewhere (Thiel and
Hoppert 2018).

2.3 Sampling for ship-based laboratory experiments

Three ship-based grazing experiments were conducted at station TF0271, where
a persistent and distinct methane enrichment below the thermocline was
detected during the cruise. These experiments were designed to examine how
(i) the abundance of copepods and (ii) their food source impact
zooplankton-associated methane production, and how (iii) the methane
production rates vary between different copepod communities. To measure
copepod species-specific methane production rates, zooplankton communities
were sampled from the surface (e.g. 20–0 m) and from the subthermocline
waters (e.g. 60–20 m). In the central Baltic Sea, these layers are commonly
dominated by Acartia spp. and T. longicornis, respectively
(Hansen et al., 2006), and will be referred to as the surface and
subthermocline communities. For the sampling hauls the cod end of the WP2 net
was sealed from outside and towed 0.1 m s−1 to reduce damage to the
zooplankton, and the content was transferred immediately into a 25 L bucket
filled with seawater from the depth where the zooplankton was sampled (i.e.
surface or subthermocline water). The zooplankton mainly comprised copepods
and was left in the cold room at 10 ∘C for an hour to allow damaged
individuals to settle to the bottom of the bucket. A subsample of living
copepods was removed gently with a 500 mL beaker from the upper layer of the
bucket to avoid injured animals, and checked for species composition under
the dissecting microscope before subsamples were used for the grazing
experiments. The sampling took place at 14:00 UTC, before vertical migration
of one of the target copepods, T. longicornis, started (Hansen et
al., 2006). This time was chosen because it was more likely that T. longicornis in the deeper water column would be starved and, thus, would
start grazing within the experiments.

Two phytoplankton compositions were used to test for the influence of the
diet on zooplankton-associated methane production: (i) a Rhodomonas
sp. (Cryptophyceae) laboratory culture, and (ii) a Nodularia spumigena
(Cyanophyceae) dominated culture from the surface mixed layer in the field,
which is typically found in these waters of the central Baltic Sea in summer
(Wasmund, 1997). The laboratory culture of Rhodomonas sp. was grown
in f/2 medium (Guillard, 1962), prepared in autoclaved bottles from
0.2 µm filtered seawater from 10 m depth. A new sub-culture was
established every 3–5 days and the inoculum was chosen to be sufficient to
keep the culture in exponential growth (cf. Knuckey et al., 2005). The second
phytoplankton culture was established from the top chlorophyll a
fluorescence maximum (0–10 m) sampled with an Apstein net (55 µm
mesh size, Hydro-Bios). The culture was re-suspended in 500 mL of seawater
and left for an hour to allow the N. spumigena cells to float on
top. The cells were carefully collected with a pipette and transferred into
an autoclaved 1 L glass bottle, which was filled up with surface seawater.
Then, 36.2 µM of NaH2PO4 as for the f/2 medium was
added. Both the Rhodomonas sp. and the N. spumigena culture
bottles were incubated in 90 L tubs, which were placed in a shaded location
on deck and continuously flushed with sea surface water at a temperature of
∼18.5∘C. A third phytoplankton culture was collected from a
subthermocline chlorophyll a peak closely below the thermocline (∼20 m depth), where mixotrophic Dinophyceae were expected to be dominant
(Carpenter et al., 1995; Hällfors et al., 2011). For this, up to 150 L
of seawater was obtained from a CTD rosette and concentrated on a
20 µm mesh. However, this culture did not grow sufficiently under
similar temperature and light conditions as in situ, and could not be used
within the grazing experiments.

Table 1Experimental conditions for the zooplankton grazing experiments
(exp.). SAphy is the specific activity of the
phytoplankton fed to the copepods. POC stands for particulate organic carbon.
No. of copepods is the average amount of copepods used in the incubation
experiments.

2.4 Phytoplankton 14C-labelling

Once a phytoplankton culture was selected for grazing experiments, three
aliquots were split between three autoclaved 1 L incubation bottles
(DURAN®, borosilicate glass 3.3, clear, GL45)
and filled up with the corresponding medium. One of these bottles was spiked
with 18.5 MBq of 14C-labelled sodium bicarbonate
(NaHCO3, 2.18 GBq mmol−1, Moravek Biochemicals, USA) for
14CH4 production measurements (Sect. 2.5.1 Methane production
and consumption rates). The other two bottles received equal amounts of
unlabelled NaHCO3 for measuring the particulate organic carbon
concentration (Sect. 2.5.2 Analysis of particulate organic carbon) and
microbial methane consumption (Sect. 2.5.1 Methane production and consumption
rates). All bottles were incubated for 3–5 days to allow cells to grow and
to take up the 14C label (Welschmeyer and Lorenzen, 1984). The
specific activity of the labelled phytoplankton (SAphy)
was measured daily by filtering 1–5 mL of the culture through a
0.45 µm cellulose nitrate filter (Millipore) and rinsing it
thoroughly with Milli-Q water. The filter was then dissolved in Filter Count
scintillation cocktail (Perkin Elmer) by vortexing and the amount of
14C label that was incorporated into particles was measured on a
liquid scintillation counter (Perkin Elmer, Tri-Carb 2800TR). Blanks for the
specific activity of the cultures were collected and analysed immediately
after the label had been added to the incubation bottle.

SAphy was calculated using Eq. (2) and used for
calculating methane production rates (de Angelis and Lee, 1994), where
SAphy is the specific activity of the phytoplankton,
Disintegrationsfilter are the disintegrations mL−1
on the filter, Volumeculture is the total volume of the
incubated culture, 6×107 dpm MBq−1 is the constant for
converting dpm into units of MBq, activityadded is the
total activity of the tracer, which was added to the incubation, and
SAtracer is the specific activity of the tracer.

2.5 Zooplankton grazing experiments

Three experiments with zooplankton grazing on phytoplankton (Table 1) were
conducted. In experiment 1 we tested whether there was (i) a linear
relationship between methane produced and the number of copepods incubated,
and (ii) a difference in methane production between the surface and
subthermocline zooplankton communities. In experiment 2 only the
subthermocline zooplankton community was used and the incubation time was
varied from 1 to 3 days to test whether the increase in methane was stable
over time and the production rate per copepod stayed constant. In experiments
1 and 2 a laboratory strain of Rhodomonas sp. (Cryptophyceae), a
standard food for copepod culturing (Dutz et al., 2008), was fed to the
zooplankton communities. Rhodomonas sp. may be considered a model
representative of the Cryptophyceae, which account for 5.5 % of the total
phytoplankton biomass in the Baltic Sea in summer 2016 (IOW monitoring
database: https://www.io-warnemuende.de/datenportal.html, last access: February 2018). In experiment 3 the
subthermocline zooplankton community was fed the cyanobacterium N. spumigena and the incubation time was varied the same way as in experiment
2. Here we selected N. spumigena as a food source, because this
species was the dominant phytoplankton in the surface waters during our field
campaign and accounted for 23 % of the phytoplankton biomass. The
different phytoplankton communities fed in these experiments allow one to
assess the impact of the food source on zooplankton-associated methane
production rates.

Each of the three grazing experiments consisted of three sets of incubations.
The first set of incubations was conducted with zooplankton grazing on
14C-labelled phytoplankton for methane production measurements
(Sect. 2.5.1 Methane production and consumption). The second set of
incubations was conducted with zooplankton grazing on unlabelled
phytoplankton to determine the food availability over the course of the
grazing experiments (Sect. 2.5.2 Analysis of particulate organic carbon).
Also, the third set of incubations was conducted with zooplankton grazing on
unlabelled phytoplankton to measure the loss of methane by microbial
oxidation under the experimental conditions (Sect. 2.5.1 Methane production
and consumption).

In selective incubations the oxygen saturation was monitored over time using
oxygen spots (5 mm, PreSens Precision Sensing) and an optode (Single Channel
Oxygen Meter, Fibox 3 LCD, PreSens Precision Sensing). The average oxygen
saturation was 75.2±2.9 % throughout the experiments.

Figure 2Schematic view of the methane stripping-oxidation line. Position 1
(displayed): the cold trap is placed in a −120∘C ethanol bath to
retain the hydrocarbons. Position 2: the cold trap is transferred into a
water bath at 90 ∘C to release the hydrocarbons towards the gas
chromatograph (GC). A detailed description is included in
Sect. S2.

2.5.1 Methane production and consumption rates

For the methane production incubations, 250 mL gastight bottles
(DURAN®, borosilicate glass 3.3, clear, GL45)
were used. The bottle lids were modified with one inlet and one outlet tube
(Fig. 2), each sealed with autoclaved silicone stoppers. The inlet tube was
long enough to reach into the lower third of the medium and had a glass frit
attached at the end. The outlet tube was short enough to remain in the
headspace of the bottle. Each bottle was filled with 50 mL of
14C-labelled phytoplankton and 3–15 mL of zooplankton stock
culture and topped up to a total volume of 200 mL with 0.2 µm
filtered seawater (Millipore GVWP filter) from either 10 or 20 m depth,
according to the depth from which the zooplankton community was obtained. All
bottles were kept in the dark at in situ temperature for 1 to 3 days in
temperature-controlled incubators. The methane, which was produced within the
time of incubation, was finally measured with a methane stripping-oxidation
line (modified following de Angelis and Lee, 1994; Fig. 2; details on the
work principle in Sect. S2). In brief, the bottles were connected to the line, the water
samples were purged with helium carrier gas and the methane (and other
hydrocarbons) was concentrated on a cold trap. After heating the trap the
methane was released and separated from other hydrocarbons by gas
chromatography (GC) and transferred to a furnace, where it was converted to
14C-labelled carbon dioxide (CO2). The 14CO2
was trapped in scintillation vials and the activity was measured by liquid
scintillation counting. Finally, the activities were used for calculating
methane production rates with Eq. (3), where
activityzoo + phy is the activity measured
in incubations containing zooplankton and phytoplankton, and
activityphy is the activity measured in blank
incubations.

14CH4producedmmol=(3)activityzoo+phyMBq-activityphyMBqSAphyMBqmmol

Blank incubations were conducted with phytoplankton and seawater only and the
volume of zooplankton was replaced with the corresponding amount of GF/F
(Whatman) filtered seawater in which the zooplankton was kept before
incubations. The CH4 concentrations of all blank incubations were
not different from the blank of the methane stripping-oxidation line
(Mann–Whitney U test, p=0.9, df=1).

Microbial methane oxidation rates were measured and the production rates
corrected accordingly. For these measurements, 14C-labelled methane
was injected into 600 mL incubation bottles, which were filled with the
corresponding volumes of plankton and water as in the incubations for methane
production measurements. The amount of produced 14CO2 was
measured according to the method of Jakobs et al. (2013). The rates were
similar in all incubations and in the range of 0.13–0.44 pM d−1.
Neither the presence of copepods nor the composition of their community or
their food had a significant influence on the methane consumption rates. In
incubations with Rhodomonas sp., methane oxidation rates were
0.13–0.39 pM d−1 and accounted for a loss of 0.2–2.3 % of the
produced methane. In incubations with cyanobacteria, the oxidation rates were
slightly higher (0.3–0.44 pM d−1).

All sets of incubations included two to three replicates. To estimate the
linear or exponential trends in methane concentration or production in
relationship with the number of copepods or time, the Gauss–Newton method
was used for minimizing the sum of squares between the fits and the
measurements (Mystat 12, Systat software).

2.5.2 Analysis of particulate organic carbon

The particulate organic carbon (POC) content in the incubations was
quantified at the beginning and end of our incubation experiments to
determine the food availability over the course of the grazing experiments.
For this, a larger volume of sample was required for later POC analysis using
a Carlo Erba Elemental Analyser (Typ EA 1110;
Carlo Erba; Nieuwenhuize et al., 1994), and 1 L
bottles (DURAN®, borosilicate glass 3.3,
clear, GL45) were used for incubations. To achieve similar concentrations of
zooplankton and phytoplankton (mL−1) as in the first set of incubations,
stock culture volumes were increased accordingly. For ambient POC analysis,
one 50 mL sample was taken from each bottle at the beginning and at the end
of the experiment on pre-combusted GF/F filters. The initial sample was
removed from the experimental bottle before the copepods were added to it,
and the final sample was taken after copepods had been removed with a
50 µm sieve. All POC measurements (Table 1) at the beginning and at
the end of the incubations exceeded the threshold for food limitation of
1–0.5 mg C L−1 (Berggreen et al., 1988). As the food was diluted
with 0.2 µm filtered seawater, all POC at the beginning of the
experiments can be assigned to the diet that was added. However, at the end
of the grazing experiments, excreted fecal pellets of the zooplankton may
have added up to the organic carbon pool. Further, it was difficult to
separate the copepods from N. spumigena by the 50 µm
sieve, as N. spumigena typically exceeds 50 µm in size. In
consequence, no grazing rates based on the decrease in POC were calculated
for the individual incubations.

Concentration profiles and stable carbon isotopes obtained in these earlier
studies indicated that the subthermocline methane enrichments resulted from
in situ production within the oxic water body. A transport from the deep
anoxic waters was excluded because the methane from this pool is efficiently
oxidized by aerobic methanotrophic bacteria situated in the oxic–anoxic
transition zone at about 100 m water depth (Jakobs et al., 2013; Schmale et
al., 2012, 2016). As their metabolism favours the turnover of
12CH4, the remaining 13CH4 becomes enriched and
δ13CCH4 values in the respective water layer are
comparably high (e.g. −40 ‰ in 80 m water depth; Jakobs et al.,
2013). In the present study, subthermocline methane enrichments in the
eastern Gotland Basin were characterized by strikingly depleted
δ13CCH4 values (−62.9 ‰ at 27 m at
TF0271, Fig. 3), supporting the idea that the pronounced methane anomaly in
this area originated from in situ biogenic production. In contrast, stable
isotope ratios of methane in the upper water column of the western Gotland
Basin showed δ13CCH4 values of −47.7 ‰
at 20 m water depth (TF0284, Fig. 3) that are close to atmospheric
equilibrium (−47 ‰).

Figure 4Development of sea surface temperatures in the central Baltic Sea
between 3 and 11 August 2016 using the oceanographic model of Gräwe et
al. (2015). The coloured dots represent the sampling stations.

Figure 5Relative zooplankton community composition of the three zooplankton
grazing experiments listed in Table 1. (a) Subthermocline (used in
experiments 1–3) and (b) surface zooplankton community composition
(used in experiment 1). Adults and copepodite stages C1–C5 were pooled for
individual species, but Nauplii were pooled together for all copepod
species.

Seasonal observations in the Baltic Sea revealed that the development of a
thermocline, which functions as a barrier and limits fluxes to the
atmosphere, was essential for the build-up of subthermocline methane
enrichments (Jakobs et al., 2014; Schmale et al., 2018). Upwelling events can
offset water column stratification through a replacement of warm, mostly
nutrient-depleted surface water by cooler and usually nutrient-enriched
subthermocline waters (Gidhagen, 1987; Lehmann and Myrberg, 2008; Reissmann
et al., 2009). Such events may also cause a rapid decline in phytoplankton
biomass in the surface water and affect the plankton composition (Vahtera et
al., 2005; Nausch et al., 2009; Wasmund et al., 2012). Upwelling
significantly increase surface water methane concentrations in the area
around Gotland during the summer (Gülzow et al., 2013; Schneider et al.,
2014). During our field campaign the sea surface temperature at station
TF0284 in the western Gotland Basin dropped from 18 to 12 ∘C, as
indicated by our oceanographic model output (Fig. 4; see also the temperature
profile of station TF0284 in Fig. 3). Assuming the thermocline was located at
18–20 m depth we estimated that the upwelled water masses must have had
originated from a depth of 25–35 m. Upwelling of cold, methane-rich
subthermocline water can plausibly explain the strong surface water methane
oversaturation observed at TF0284 (saturation value of 198 %). The other
stations were not affected by upwelling events during the time of sampling.
Even though our oceanographic model output indicated that the water mass at
station TF0283 (sampled on 11 August) was located at the upwelling front
(Fig. 4), our field measurements showed that the station was not affected by
the event, as there is no drop in the surface water temperature visible
(Fig. 3). However, our study indicates that in contrast to the deep water
methane pool, which is efficiently separated from the surface water through
the halocline at about 60 m depth (Schmale et al., 2010; Jakobs et al.,
2014), upwelling of subthermocline waters has to be considered an important
mechanism that contributes to the sea–air methane fluxes in the Baltic Sea.

3.2 Controls on zooplankton associated methane production

We obtained species- and food-specific methane production rates in
incubations, which contained field copepods (surface and subthermocline
communities, Fig. 5) in nearly natural abundances (1.5–8.5 times the natural
density) by using the methane stripping-oxidation line. We found a
substantial increase in methane production with the number of copepods in the
incubations, but no production in controls containing phytoplankton only
(Fig. 6). This implies that the production of methane is associated with the
active grazing of zooplankton.

Figure 6(a) Experiment 1: methane production as a function of the
number of copepods in the surface (dominated by Acartia spp.) and
subthermocline zooplankton communities (dominated by Temora longicornis). (b) Experiments 2 and 3: copepod-specific methane
production over time when using the cryptophyte alga Rhodomonas sp.
(experiment 2) or the cyanobacterium Nodularia spumigena (experiment
3) as food sources.

The incubations with a high proportion of T. longicornis had higher
production rates than the Acartia spp. dominated setups (125±49 vs. 84±19 fmol CH4 copepod−1 d−1). This
indicates that methane production may depend on the composition of the
zooplankton community (Fig. 6a). However, the differences were not
significant (Kruskall–Wallis test; p=0.150, df=1), which may be
a consequence of the limited number of incubations. Similar observations were
made in laboratory experiments using cultured species from the North Atlantic
(de Angelis and Lee, 1994). These authors observed methane production in all
experiments for T. longicornis grazing on phytoplankton, but not for
Acartia tonsa. These differences may be due to species-specific
differences in grazing rates, food preferences and gut floras. Furthermore,
the methane production rates per copepod reported by de Angelis and
Lee (1994) were 2 orders of magnitude higher
(4–20 pmol CH4 copepod−1 d−1) than the rates
measured in our experiments. Still, our results are in agreement with those
of previous zooplankton incubation experiments conducted in the central
Baltic Sea (0.3 pmol CH4 copepod−1 d−1, Schmale et
al., 2018). This similarity is notable as the previous experiments used
zooplankton abundances that were about 1000 times higher than the natural
density in the field. The obvious discrepancy from the methane production
rates reported by de Angelis and Lee (1994) might be related to the
physiological differences (e.g. animal size) between the copepods used
(length T. longicornis North Atlantic: 1300 µm vs. Baltic
Sea: 700 µm). The methane production rates may also be lower for
younger development stages of copepods, which contributed to the natural
surface community used in our incubations (Fig. 5). Animal size affects the
oxygen gradient in the guts of these copepods and affects the dimension of
produced fecal pellets and, thus, the penetration depth of oxygen into the
pellet (Ploug and Jörgensen, 1999; Tang et al., 2011). Alternatively,
lower methane production rates observed in our experiments may have reflected
a response of the animals to stress of being removed from their natural
environment. In contrast to the study of de Angelis and Lee (1994), who used
cultured animals in their experiments, we immediately transferred the field
copepods into incubation bottles and fed phytoplankton that were not
representative of the phytoplankton biomass of the Baltic Sea (i.e. the
cryptophyte Rhodomonas sp.) and thus did not belong to their natural
food source. To lower the capture stress, we selected a rather gentle method
for sampling, and we avoided food shortage, which was shown to be more
influential on the decrease in physiological rates (Ikeda and Skjoldal,
1980). Also, we used a food source which was previously shown to be of good
quality (e.g. Knuckey et al., 2005; Koski and Breteler, 2003). Another factor
which may have led to lower methane production rates than measured by de
Angelis and Lee (1994) is the quality of the filtered seawater used in the
incubations. In our experiments we used filters with a pore size of
0.2 µm, while de Angelis and Lee (1994) used filters with a pore
size of 1.2 µm to prepare the incubation water. Our intention was
to exclusively investigate the methane production by zooplankton while
minimizing the influence of particulate material (e.g. fecal pellets) in the
seawater. However, we are aware that the smaller pore size used in our
studies reduced the number of bacteria in the incubation water, which may
have been important for the methane production outside the body of the
copepods.

Figure 8Surface phytoplankton community composition integrated over the
upper 10 m of the water column (mg C m−3) at stations with a distinct
(a) and without a distinct (b, c) subthermocline methane
enrichment. The grey shaded non-cyanobacteria community is described in
detail in the coloured circles.

Figure 9Phytoplankton community composition within the subthermocline
chlorophyll a maximum (mg C m−3) at three stations with a distinct
subthermocline methane enrichment (a–e) and at one station without
a distinct enrichment (f). The grey shaded non-cyanobacteria
community is described in detail in the coloured circles. Three replicate
samples were taken at TF0271 in a period of 7 days (a–c) showing
that the prevalence of Dinophyceae below the thermocline is a consistent
feature at this station.

Measurable methane production occurred when the T. longicornis-dominated community was fed on Rhodomonas sp., while no
production occurred when it was fed on the cyanobacterium N. spumigena (Fig. 6b). In fact it appears that these cyanobacteria are a
rather negligible food source for planktonic herbivores due to their toxic
properties, large size, and low lipide concentrations (Sellner et al., 1994;
Eglite et al., 2018). Our experiments therefore reveal that the availability
of a suitable phytoplankton diet is an important control on the
zooplankton-associated methane production.

The observed exponential increase in methane with increasing incubation time
implies that zooplankton-associated methane production is a continuous
process (Fig. 6b). In addition, we measured a linear increase in the methane
production rates per individual with increasing incubation time (Fig. 7).
Potential explanations include (1) a delay in grazing by stress through
experimental conditions, (2) the accumulation of fecal pellets within the
incubation bottles followed by methane production in anoxic
microenvironments, and (3) enhanced methane production through release of
methane precursor substances from fecal pellets or from disrupted
phytoplankton cells into the incubation water. In the first case we would
expect the production rates to stabilize within the 3 days of the experiment;
instead, we observed a linear increase and a rather low variability among the
replicates. In the second case, the fecal pellets could temporarily act as
anoxic microenvironments for methanogenic archaea (Oremland et al., 1979;
Bianchi et al., 1992; Marty et al., 1993; Karl and Tilbrook, 1994; Ditchfield
et al., 2012). However, it is debatable whether anoxic conditions can persist
within fecal pellets outside of the anoxic digestive
tracts of the copepods (Ditchfield et al., 2012;
Ploug et al., 2008). For T. longicornis fed on Rhodomonas
sp., the diffusive boundary layer of the fecal pellets through which the
exchange of gases occurs was shown to be very thin, and no indications of
anoxic conditions were detected (Ploug et al., 2008). Studies investigating
the anoxic potential within particle aggregates were only able to confirm
anoxic conditions in the interior of nutrient- and carbon-rich particles
>600µm and suggest that anoxia in marine aggregates
is more likely to occur in an oxygen-depleted water column (Ploug et al.,
1997; Ploug et al., 2001). On our cruise, a fecal pellet size of only
<150µm was measured for the surface and subthermocline
zooplankton communities. We therefore suggest that anaerobic methanogenesis
by archaea thriving within fecal pellets played only a minor role. Instead,
continuous release of methanogenic substrates (like organic sulfur compounds)
by cell disruption during feeding, defecation, or diffusion from fecal
pellets may have resulted in an enrichment of these substances in the
incubation water, and fostered a subsequent microbial turnover of these
precursors outside the body of the copepod.

Figure 10Average zooplankton community composition between the sea surface
and the halocline for stations with distinct (left bars) and without distinct
(right bars) subthermocline methane enrichments. Three replicate samples were
taken at station TF0271 in a period of 10 days to investigate the temporal
variability in the community composition at this location.

3.3 Organic sulfur compounds as possible substrates for methane production in oxic waters

The phytoplankton community composition in the surface (Fig. 8) and
subthermocline waters (Fig. 9) was similar at all investigated stations
during our field campaign. However, the phytoplankton biomass was lower at
station TF0284, which was recently influenced by an upwelling event. Hence,
it needs to be considered that also the phytoplankton composition at this
station could have been altered by the event. Dinophyceae, in particular the
mixotrophic Dinophysis norvegica, were more abundant at stations
with a distinct subthermocline methane enrichment. They produce relatively
high amounts of DMSP and DMSO compared to the other phytoplankton species
observed within our study (Keller et al., 1989; Hatton and Wilson, 2007;
Caruana and Malin, 2014). Also, positive correlations have previously been
observed between DMSP and CH4 and DMSO and CH4 in the
surface ocean (Zindler et al., 2013). Damm et al. (2010) suggested that the
microbial metabolization of DMSP and its degradation products dimethylsulfide
(DMS) and methanethiol to methane is favoured under nitrogen-stressed
conditions in oligotrophic waters. In the central Baltic Sea the dissolved
inorganic nitrogen pool that builds up over the winter months is already
exhausted after the first spring bloom in the photic zone and leaves behind
nitrogen-stressed conditions for phytoplankton taxa, which are unable to fix
molecular nitrogen (Schneider et al., 2009). These nitrogen-stressed
conditions can lead to an accumulation of DMSP in phytoplankton cells (Sunda
et al., 2007) that exceeds 10 % of the cell carbon (Matrai, 1994). In the
central Baltic Sea a pronounced DMS maximum was detected during summer months
in the surface waters (Leck et al., 1990). No correlation was identified
between high DMS concentrations and any particular phytoplankton species.
Instead, DMS production in the surface water was accelerated through
phytoplankton growth under nitrogen-limited conditions, and correlated
significantly with copepod and total zooplankton biomass. Hence, the release
of DMSP, DMSO and DMS from phytoplankton was suggested to be controlled by
zooplankton and heterotrophic bacteria (Leck et al., 1990; Kwint et al.,
1996; Wolfe et al., 1997; Simo et al., 2002; Lee et al., 2003).

Figure 11GC–MS chromatograms of neutral lipids (methyl ester/TMS
derivatives) from mixed-layer phytoplankton (a) and subthermocline
zooplankton (b) at station TF0271 (with a distinct subthermocline
methane enrichment). Data from subthermocline zooplankton at TF0250 (without
a distinct subthermocline methane enrichment) are shown as a
reference (c). Main compounds are labelled and interpreted as
follows (see text for further discussion); 16:0, n-hexadecanoic acid
(unspecific, high in bacteria); 14OH ∕ 16OH, n-tetradecanol and n-hexadecanol (copepod wax
esters); 18:1, oleic acid (unspecific, high in heterotrophs but also in
(cyano)bacteria); 20:5, n-eicosapentaenoic acid (phytoplankton, high in
diatoms); Std, internal standard; 22:6, n-docosahexaenoic acid
(phytoplankton, high in Dinophyceae); 265,22, 24-norcholesta-5,22-dien-3β-ol
(specific for Dinophyceae); 275, cholesterol (unspecific, high in
zooplankton, but also found in some algae including Dinophyceae). Compounds
indicating contributions from Dinophyceae-derived lipids are highlighted with
an arrow. Note enhanced levels of these biomarkers in T. longicornis-dominated zooplankton at the station with a distinct
subthermocline methane enrichment (TF0271).

Similar to phytoplankton, zooplankton, in particular copepods, may use DMSP
for osmoregulation and were shown to increasingly assimilate DMSP at higher
salinities (Tang et al., 1999). Likewise, DMSP ingestion by copepods
increased with increasing DMSP content of the food (Tang et al., 1999). De Angelis and Lee (1994) showed that T. longicornis feeding on Dinophyceae (Prorocentrum minimum) resulted
in the highest methane production rates per copepod, which suggests a link
between the DMSP/DMSO content of the diet and zooplankton-associated methane
production. Based on the observed zooplankton and phytoplankton distributions
(Figs. 8, 9 and 10), we speculate that the development of distinct
subthermocline methane enrichments in the central Baltic Sea is influenced by
the combination of T. longicornis and relatively high abundances of
Dinophyceae.

To retrieve further information about potential trophic relationships between
T. longicornis and Dinophyceae, lipid biomarkers of concentrated
plankton samples from two depths, the surface layer and subthermocline waters
were analysed. Also, samples from stations with (TF0271) and without (TF0250)
distinct subthermocline methane enrichment were compared. Although individual
fatty acids have to be assigned cautiously to specific taxonomic groups, the
distribution of these compounds in copepod neutral lipids has been shown to
largely reflect the lipid composition of the prey (Peters et al., 2013).
Figure 11a shows the neutral lipids extracted from the surface-layer
phytoplankton obtained at station TF0271. The fatty acids contained in
samples from this depth revealed major contributions from cyanobacteria
(typically high in 16:0 and C18 fatty acids), diatoms (high in
20:5), and Dinophyceae (22:6; cf. Peters et al., 2013), which corresponds
to the phytoplankton community composition observed at this station by
microscopy (Fig. 8a). The relatively high abundance of Dinophyceae in the
surface layer was further reflected in the presence of
24-norcholesta-5,22-dien-3β-ol (265,22), an unusual sterol that is regarded
as a specific marker for these algae in temperate waters (Rampen et al.,
2007).

Compounds extracted from the subthermocline zooplankton community at station
TF0271, dominated by T. longicornis (52 %), revealed a broad
similarity to the phytoplankton-derived lipids, and
reflected the diurnal feeding behaviour of these copepods in the surface
mixed layer (Fig. 11b). Notably though, lipids of putative dinophyte origin
were considerably enriched, supporting the idea of a preferential uptake of
these algae by T. longicornis. In contrast, mixed zooplankton
obtained at reference station TF0250 contained few T. longicornis
(10 %) but relatively more Acartia spp. (37 %) and
Pseudocalanus spp. (32 %). This sample showed much lower
relative amounts of the Dinophyceae-derived biomarkers 22:6ω3 and
265,22, indicating only a minor importance of this food source at the
reference station (Fig. 11c). Altogether, our biomarker data further
corroborate our suggestion that the feeding of T. longicornis on
(DMSP/DMSO-rich) Dinophyceae may be an essential factor in the development of
subthermocline methane enrichments in the central Baltic Sea.

We further assume that zooplankton-associated production of fecal pellets and
the transit of these pellets through the water column play a critical role in
the build-up of the pool of organic sulfur compounds in the central Baltic
Sea. Sinking velocities are low for pellets produced from Dinophyceae (Hansen
and Bech, 1996; Thor et al., 2003). Hence, we propose that high degradation
rates of those fecal pellets and an efficient microbial turnover of the
contained organic sulfur compounds (e.g. DMSP; Tang, 2001)
contribute to the subthermocline methane enrichment. The gradual loss of
organic sulfur compounds from fecal pellets could plausibly explain the
increase in copepod-specific methane production over time, as measured in our
incubation study (Figs. 6b and 7). Unfortunately, no Dinophyceae culture was
available for our field experiments, because of their relatively low growth
rates (Carpenter et al., 1995) and mixotrophic feeding requirements (Tong et
al., 2010) that did not allow an adequate radio labelling of the culture with
sodium bicarbonate. Likewise, the relatively low production rates observed in
our experiments could be explained by the lack of appropriate substrates for
methane production, as Cryptophyceae (i.e. Rhodomonas sp.) contain
only low amounts of DMSP as compared to other phytoplankton groups (Dong et
al., 2013). Furthermore, we used 0.2 µm filtered seawater in our
incubations, which was depleted in microorganisms. However, these
microorganisms might be relevant for the turnover of DMSP to methane outside
of the copepod bodies.

Several processes that produce methane in oxic waters have been recently
identified and it is assumed that climate change will impact their source
strength, with far-reaching consequences for methane flux and climate
feedback. However, mechanisms and magnitudes of these sources remain vague.
Based on our findings, we conclude that zooplankton contributes to
subthermocline methane enrichments in the central Baltic Sea by (1) direct
methane production within the digestive track of copepods and/or (2) indirect
contribution to methane production through release of methane precursor
substances into the surrounding water, followed by microbial degradation to
methane outside the copepod's body. Further, our field observations combined
with lipid biomarker studies indicate that a distinct food web segment
consisting of DMSP-rich Dinophyceae and the copepod T. longicornis
may foster the build-up of methane anomalies in oxic waters of the central
Baltic Sea. For future studies, we recommend using unfiltered in situ water
for the incubations. We further suggest cultivating Dinophyceae under
controlled laboratory conditions before the field campaign and feeding these
radio-labelled organisms to in situ copepods directly after sampling in the
field. These incubations should be accompanied by a quantification of the
DMSP and DMS content in phytoplankton and zooplankton as well as in the water
column.

BS, OS, and SO designed and built the methane
stripping-oxidation line and performed the incubation experiments. JW and NLW
supported the plankton sampling and the grazing experiments. VT and AKW
conducted the lipid biomaker analysis. UG performed the oceanographic
modelling of the upwelling event. SS performed the stable carbon isotope
analyses. GR, ML, and NW helped with the data analyses and interpretation.
All the authors co-wrote the manuscript.

We thank Nicole C. Power Guerra for her help at sea and in the laboratory. We
would also like to thank Michael Glockzin for producing the map and Juha
Hatakka (Finnish Meteorological Institute) for providing the atmospheric
methane concentration data from station Utö. Further, we appreciate the
critical comments by Jörg Dutz. We thank the captain and crew of R/V
Alkor for technical support. This work was supported by the German
Research Foundation (DFG) through grant SCHM 2530/5-1 to Oliver Schmale, DFG
grant LA 1466/10-1 to Matthias Labrenz, and DFG grant LO 1820/4-1 to Natalie Loick-Wilde.

The publication of this article was funded by the Open Access Fund of the Leibniz Association.

The understanding of surface water methane production in the world oceans is still poor. By combining field studies and incubation experiments, our investigations suggest that zooplankton contributes to subthermocline methane enrichments in the central Baltic Sea by methane production within the digestive tract of copepods and/or by methane production through release of methane precursor substances into the surrounding water, followed by microbial degradation to methane.

The understanding of surface water methane production in the world oceans is still poor. By...